Title of article :
Automatic determination of seamlines for aerial image mosaicking based on vector roads alone
Author/Authors :
Wan ، نويسنده , , Youchuan and Wang، نويسنده , , Dongliang and Xiao، نويسنده , , Jianhua and Lai، نويسنده , , Xudong and Xu، نويسنده , , Jingzhong، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
Image mosaicking is defined as the registration of two or more images that are then combined into a single image. One of the most difficult steps in the automatic mosaicking of orthoimages is deciding where to place seamlines in overlapping regions. Based on millions of image pixels, existing seamline detection methods mainly focus on how to avoid crossing buildings that are higher than the ground, which results in parallax on the overlapping images. However, various data in vector format, such as vector roads plotted manually and precisely, have not been used to aid the selection of seamlines. This paper presents a novel approach using vector roads alone to generate seamlines, and describes its application to the automatic generation of seamlines for image mosaicking of the city of Wuhan, China. A representative seamline is extracted as follows. First, the skeleton of the overlapping region of adjacent images is extracted after the delineation of boundaries of individual images. Second, vector roads in the overlapping region are overlaid with the extracted skeleton to build a weighted graph G (V, E). Finally, the Floyd–Warshall algorithm is applied to find the lowest cost path from I to O, which refer to two intersections of adjacent image polygons, with the lowest-cost path being the seamline. This vector-based approach is typically more efficient than raster-based approaches. Experiments demonstrate the merits of the proposed approach especially when vector road networks are available.
Keywords :
Seamlines extraction , Vector roads , Image mosaicking , Aerial photogrammetry
Journal title :
ISPRS Journal of Photogrammetry and Remote Sensing
Journal title :
ISPRS Journal of Photogrammetry and Remote Sensing